Identifying and Analyzing Factors Affecting the Productivity Enhancement of Power Company Employees Based on Artificial Intelligence

The primary objective of this article is to identify and analyze the factors influencing the productivity enhancement of power company employees based on artificial intelligence. The research method employed is qualitative. In addition to document analysis, thematic analysis was conducted using MAXQDA12 software to identify the relevant factors and components. The statistical population of this study included all experts in the field of educational management as well as managers and specialists in the power company. Theoretical saturation was achieved after conducting 14 interviews. The duration of the interviews ranged from 75 to 120 minutes. Ultimately, basic, organizing, and overarching themes were extracted. Based on the semi-structured interviews, 10 dimensions (knowledge and technology management improvement, human resource management reinforcement, organizational process recognition, financial resource process enhancement, smart planning improvement, ethical intelligence, training level enhancement, increased capacity for change and transformation, individual skill improvement, and decision-making improvement), 24 components (organizing themes), and 100 indicators were identified for enhancing employee productivity in the power company based on artificial intelligence. The results indicated that the majority of experts believed artificial intelligence positively influences productivity enhancement, with the most significant contributing factor being the improvement of individual skills.